EC3 Bias Patterns.
Another visualization design challenge is how to communicate hidden patterns and outliers in the data.
While individual labels can expose problematic bias, a whole set of semantically similar labels which are all biased towards a certain direction poses an even bigger fairness problem.
Here, similarity information for labels has to be considered and displayed in a way that lets domain experts reason about individual instances as well as bigger bias problems throughout the models and for different sensitive attributes [1]}, [2]}.
Again, this is especially important in our setting, where the label space is large, and there exist many related labels.
